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--- |
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license: other |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B |
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datasets: |
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- scitldr |
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model-index: |
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- name: Llama-3-8B-Summarization-QLoRa |
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results: [] |
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pipeline_tag: summarization |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Llama-3-8B-Summarization-QLoRa |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the scitldr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4051 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.226 | 0.5020 | 500 | 2.3232 | |
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| 2.2207 | 1.0040 | 1000 | 2.3130 | |
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| 1.6901 | 1.5060 | 1500 | 2.4051 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
